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Improved individual and population-level HbA1c estimation using CGM data and patient characteristics

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by...

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Détails bibliographiques
Publié dans:J Diabetes Complications
Auteurs principaux: Grossman, Joshua, Ward, Andrew, Crandell, Jamie L., Prahalad, Priya, Maahs, David M., Scheinker, David
Format: Artigo
Langue:Inglês
Publié: Elsevier Inc. 2021
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC8316291/
https://ncbi.nlm.nih.gov/pubmed/34127370
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jdiacomp.2021.107950
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